Stochastic Processes with R: An Introduction
cuts through the heavy theory that is present in most courses on random processes and serves as practical guide to simulated trajectories and real-life applications for stochastic processes. The light yet detailed text provides a solid foundation that is an ideal companion for undergraduate statistics students looking to familiarize themselves with stochastic processes before going on to more advanced courses.
Key Features
Provides complete R codes for all simulations and calculations
Substantial scientific or popular applications of each process with occasional statistical analysis
Helpful definitions and examples are provided for each process
End of chapter exercises cover theoretical applications and practice calculations